Bioconductor

Lessons from switching to on-disk storage using DelayedArray containers

DelayedArray: A tibble for arrays

Bioconductor 3.7 release and the DelayedArray framework

Today marks the release of Bioconductor 3.7 (official announcement). Congratulations to the hundreds of developers who have collectively developed more than 1500 software packages, not to mention the annotation, experiment data, and workflow packages. A huge thank you to the core team for the incredible work they do, especially around release time! Much of my recent development work on Bioconductor has been leveraging and extending the DelayedArray framework developed by Hervé Pagès (Bioconductor Core Team).

R

Some of the things I’ve done with R

Scaling R and Bioconductor to support methods for single-cell genomic analysis

DelayedMatrixStats: Porting the matrixStats API to work with DelayedMatrix objects

GenomicTuples and DNA methylation patterns

BioC2017 Developer Day

A couple of weeks back I was in Boston for BioC2017, the annual Bioconductor meeting. This is my favourite conference because I get to hear from and meet the awesome community that develop and use R/Bioconductor packages to enable research in high-throughput biology. The agenda and slides for the 3 days are available from https://www.bioconductor.org/help/course-materials/2017/BioC2017/. I’m drawing on these notes that I scrawled during Developer Day, the first day of the meeting.